The field of the disclosure relates generally to surveillance data analysis, and more specifically, to methods and systems for estimating, from surveillance observations, the costs of actions perceived by the subject of observation, and detecting anomalous or otherwise interesting subject behavior, based on the action cost estimates.
Analysis of surveillance data is a major bottleneck in improving the situational awareness in security applications. Such security applications can be considered to range from public space surveillance to war theatre surveillance operations. Specifically, there is an abundance of video data available to consumers of such data, many times more than there are available man-hours to watch such video data. Automating analysis tasks is therefore a highly desirable goal. Among the tasks of an intelligence analyst is to determine what an observable agent (a person, or, by extension, a vehicle) intends to do, based on its previous behavior. Such observation is typically from video or radar. Another task, usually preceding the determination of intent, is simply identifying, from a large set of actors, those behaving suspiciously and warranting further attention.
This disclosure enables computational behavior analysis for agents that behave sub-optimally due to their imperfect perception of environment and/or action costs. Moreover, it allows inference about the likely percepts available to the agent.